The phase noise is an inherent characteristic of any signal generator which consists in a random uncontrolled variation of a generated signal phase in time. In the case of a communication system the phase noise of the reference oscillators at the transmitter and receiver sides leads to uncontrolled changes in the received signal phase in time which has to be estimated and compensated to provide reliable and valid reception of the transmitted data.
The phase noise is typically significant in oscillators based on semiconductor integrated circuits that are widely applied in modern wireless systems due to their low cost, small size and low power consumption. Wherein a phase noise level is higher for high frequency oscillators, e.g. for 60-90 GHz millimeter-wave band communication systems demonstrating an increasing growth of usage.
A basic scheme of data transmission in a wireless communication network is a single carrier scheme where information bits are transmitted with their modulation to time-domain signal symbols. A general scheme of a digital communication system with a single carrier is presented in FIG. 1. An information message in such scheme is encoded and modulated in the time domain via the digital signal processing. Then the signal samples are transformed to an analog baseband signal by a Digital-to-Analog Convertor (DAC) whereupon the baseband signal is moved to the carrier frequency, passed through a power amplifier and supplied to a transmitter antenna. At the receiver side the passband signal that is passed through the wireless channel arrives at a low-noise amplifier (LNA) and is transformed to a baseband signal using a backward frequency transfer. The baseband signal samples are converted to the digital form by an Analog-to-Digital Converter (ADC) for further digital signal processing at the receiver. The digital part of the receiver performs time and frequency synchronization of the received signal, channel equalization (elimination of channel linear distortions), phase noise estimation and compensation and data decoding based on the output of a digital demodulator. A traditional approach to phase noise mitigation at the receiver in such systems consists in application of a Phase-Lock-Loop (PLL) scheme performing phase noise suppression with a feedback loop including the following operations: signal demodulation, i.e. estimation of a phase noise sample for the symbol being demodulated, low-pass filtering of the phase noise samples, and application of the filtered phase noise estimates for phase error compensation at next symbols of the received signal. The phase error compensation can be done both after (FIG. 1) and before the signal equalization (FIG. 2).
The described traditional method of the phase noise compensation in single carrier communication systems requires phase noise estimation for each transmitted symbol (using data symbols and a decision-directed approach based on the demodulator output) or for a significant part of the symbols (using pilot symbols in the transmitted signal) for its efficient operation.
Besides, using phase information obtained from the demodulated data may typically be insufficiently reliable (i.e. the phase estimates may contain a sufficiently high level of errors) and the pilot samples known to the receiver may stand apart from each other by a significant number of signal samples. For example, insertion of pilot signals only to form guard cyclic prefixes is common in Single Carrier systems with Frequency Domain Equalization (SC-FDE). This modulation type assumes block data transmission and is similar to Orthogonal Frequency Division Multiplexing (OFDM). The SC-FDE modulation type is widespread in modern wireless communication systems.
For the indicated case of a sufficient time interval between the pilot signals the phase error estimation can be done using the known pilot signals and then the phase errors can be approximated for signal samples carrying the data using a constant or linear interpolation. However, such phase noise estimation may be not enough accurate, since the phase noise realization can significantly deviate from a constant value or a linear trend. Therefore, there is a need for a more accurate method for estimation and approximation of the phase noise realizations between the values estimated from the pilot signals. In particular, values of the phase noise realization at different signal samples are not independent but are correlated in time that can be used to improve an estimation accuracy.
A method for reduction of phase noise impact on a quality of received signal in single carrier systems is disclosed in U.S. Pat. No. 7,409,024 “Process for providing a pilot aided phase synchronization of carrier” published Aug. 5, 2008. A general structure of the apparatus disclosed in the patent is presented in FIG. 3. The method proposed in the patent includes estimation of phase distortions at pilot sample blocks of the equalized signal using a procedure of the Weinner filtering of phase errors, calculation of phase errors for the data samples with the linear interpolation of phase error estimates from the two neighboring pilot blocks and phase noise compensation with the calculated values. A drawback of the proposed method consists in a fact that the Werner filtering procedure relying on the phase noise correlation properties is efficiently used only to improve the phase noise estimation for the pilot samples and is not applied to the phase error estimation for the data samples located between the pilot samples. Efficiency of the method disclosed in the patent applied to the data samples is comparable with the performance of the previously considered linear interpolation scheme because in both cases essentially the same algorithm is used which does not provide tracking of significant deviations of the noise from the linear trend between the groups of pilot samples of a single block.
The prior art includes another technical solution presented in U.S. Pat. No. 7,733,993 “High speed gain and phase recovery in presence of phase noise” and providing a method of phase noise compensation in OFDM systems. The method disclosed in the patent assumes estimation of subcarrier phase distortions for an OFDM block in the frequency domain based on knowledge of pilot samples and application of hard decisions for the data subcarriers, conversion of phase error estimates from the frequency domain to the time domain via the Discrete Fourier Transformation (DFT) and smoothing of the obtained estimates via the Kalman filtering (FIG. 4). However, the presented method is not applicable in the single carrier systems because it uses specific properties of the OFDM systems, namely, it performs estimation of phase noise spectral components in the frequency domain based on knowledge of the pilot samples and making hard decisions for the data symbols which is impossible in the single carrier systems with the transmitted signal being formed in the time domain.
The prior-art also includes a phase noise mitigation method for single carrier data transmission systems disclosed in U.S. Pat. No. 9,160,382 “Phase noise mitigation for wireless communications”. The method described in the patent is considered as a prototype of the present invention. It assumes estimation of phase noise distortions for each sample of the received signal based on knowledge of the pilot samples and usage of hard decisions for the data symbols, filtering of the estimated phase errors for each sample using the Joint Forward Backward Linear Prediction Filter (JFBLPF) and compensation of the phase noise by the filtered smoothed sequence of the phase errors. In order to improve the phase noise compensation efficiency, iterative execution of the method is additionally proposed to get more accurate estimates of the phase distortions for the data signal samples. A general scheme of a receiver using an apparatus described in U.S. Pat. No. 9,160,382 is presented in FIG. 5 and the apparatus that implements the method disclosed in the patent is represented in FIG. 6. Drawbacks of the method include high computational complexity of its implementation requiring inversion of large matrices which is prohibitive for application in most of practical wireless communication systems. It should also be noted that the method uses statistical characteristics of the phase noise to improve accuracy of estimation of its realization. However, these characteristics are preliminary estimated from the same set of data which worsens the accuracy of the phase noise estimation and compensation. At the same time such statistical characteristics are a priori known for most of generators used in radio communication systems e.g. in the form of the phase noise power spectral density or the equivalent phase noise spectrum bandwidth and can be taken into account within the estimation process.
Thus, there is a necessity for a method of phase noise estimation and compensation in wireless communication systems where pilot signals (or groups of pilot signals) known to the receiver are separated by sufficient time intervals, so that a realization of the phase noise cannot be accurately approximated by a constant or a linear trend. At the same time a priori known statistical characteristics of reference oscillators should be used for the phase noise estimation and estimation accuracy improvement, for example, the power spectral density of the phase noise or its derivative characteristics. This method of the phase noise suppression should have a relatively low computational complexity compared to analogs from the prior art that can provide a possibility of its implementation in FPGA or ASIC with limited hardware resources.